b'Apple Inc.'

research

∙ 08/28/2021

DKM: Differentiable K-Means Clustering Layer for Neural Network Compression

Deep neural network (DNN) model compression for efficient on-device infe...

Minsik Cho, et al. ∙

research

∙ 06/18/2020

Set Distribution Networks: a Generative Model for Sets of Images

Images with shared characteristics naturally form sets. For example, in ...

Shuangfei Zhai, et al. ∙

research

∙ 01/09/2020

Least squares binary quantization of neural networks

Quantizing weights and activations of deep neural networks results in si...

Hadi Pouransari, et al. ∙

research

∙ 06/15/2022

Rethinking Initialization of the Sinkhorn Algorithm

Computing an optimal transport (OT) coupling between distributions plays...

James Thornton, et al. ∙

research

∙ 12/06/2019

Geometric Capsule Autoencoders for 3D Point Clouds

We propose a method to learn object representations from 3D point clouds...

Nitish Srivastava, et al. ∙

research

∙ 11/09/2019

Worst Cases Policy Gradients

Recent advances in deep reinforcement learning have demonstrated the cap...

Yichuan Charlie Tang, et al. ∙

research

∙ 11/05/2021

Reconstructing Training Data from Diverse ML Models by Ensemble Inversion

Model Inversion (MI), in which an adversary abuses access to a trained M...

Qian Wang, et al. ∙

research

∙ 02/04/2022

Learning Representation from Neural Fisher Kernel with Low-rank Approximation

In this paper, we study the representation of neural networks from the v...

Ruixiang Zhang, et al. ∙

research

∙ 10/31/2018

Democratizing Production-Scale Distributed Deep Learning

The interest and demand for training deep neural networks have been expe...

Minghuang Ma, et al. ∙

research

∙ 12/12/2019

One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment

PointNet has recently emerged as a popular representation for unstructur...

Vinit Sarode, et al. ∙

research

∙ 03/09/2020

Unsupervised Style and Content Separation by Minimizing Mutual Information for Speech Synthesis

We present a method to generate speech from input text and a style vecto...

Ting-yao Hu, et al. ∙

research

∙ 10/09/2019

3D Manhattan Room Layout Reconstruction from a Single 360 Image

Recent approaches for predicting layouts from 360 panoramas produce exce...

Chuhang Zou, et al. ∙

research

∙ 04/02/2019

MVX-Net: Multimodal VoxelNet for 3D Object Detection

Many recent works on 3D object detection have focused on designing neura...

Vishwanath A. Sindagi, et al. ∙

research

∙ 02/16/2021

Non-Autoregressive Text Generation with Pre-trained Language Models

Non-autoregressive generation (NAG) has recently attracted great attenti...

Yixuan Su, et al. ∙

research

∙ 12/02/2021

Robust Robotic Control from Pixels using Contrastive Recurrent State-Space Models

Modeling the world can benefit robot learning by providing a rich traini...

Nitish Srivastava, et al. ∙

research

∙ 10/15/2021

Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text

Named entity disambiguation (NED), which involves mapping textual mentio...

Maya Varma, et al. ∙

research

∙ 09/17/2021

Enforcing fairness in private federated learning via the modified method of differential multipliers

Federated learning with differential privacy, or private federated learn...

Borja Rodríguez Gálvez, et al. ∙

research

∙ 06/30/2020

Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution

Knowledge distillation has been used to transfer knowledge learned by a ...

Hadi Pouransari, et al. ∙

research

∙ 12/07/2018

Nonlinear Conjugate Gradients For Scaling Synchronous Distributed DNN Training

Nonlinear conjugate gradient (NLCG) based optimizers have shown superior...

Saurabh Adya, et al. ∙

research

∙ 01/28/2020

Towards Learning Multi-agent Negotiations via Self-Play

Making sophisticated, robust, and safe sequential decisions is at the he...

Yichuan Charlie Tang, et al. ∙

research

∙ 02/12/2020

Capsules with Inverted Dot-Product Attention Routing

We introduce a new routing algorithm for capsule networks, in which a ch...

Yao-Hung Hubert Tsai, et al. ∙

research

∙ 06/06/2022

Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation

While large-scale neural language models, such as GPT2 and BART, have ac...

Jin Xu, et al. ∙

research

∙ 07/27/2022

GAUDI: A Neural Architect for Immersive 3D Scene Generation

We introduce GAUDI, a generative model capable of capturing the distribu...

Miguel Angel Bautista, et al. ∙

research

∙ 02/08/2022

Fair SA: Sensitivity Analysis for Fairness in Face Recognition

As the use of deep learning in high impact domains becomes ubiquitous, i...

Aparna R. Joshi, et al. ∙

research

∙ 03/18/2022

Learning Compressed Embeddings for On-Device Inference

In deep learning, embeddings are widely used to represent categorical en...

Niketan Pansare, et al. ∙

research

∙ 03/22/2022

Open-Vocabulary DETR with Conditional Matching

Open-vocabulary object detection, which is concerned with the problem of...

Yuhang Zang, et al. ∙

research

∙ 04/05/2022

Improving Voice Trigger Detection with Metric Learning

Voice trigger detection is an important task, which enables activating a...

Prateeth Nayak, et al. ∙

research

∙ 11/12/2018

Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces

Word embedding techniques heavily rely on the abundance of training data...

Victor Prokhorov, et al. ∙

research

∙ 03/23/2022

NeuMan: Neural Human Radiance Field from a Single Video

Photorealistic rendering and reposing of humans is important for enablin...

Wei Jiang, et al. ∙

research

∙ 03/29/2022

Enabling hand gesture customization on wrist-worn devices

We present a framework for gesture customization requiring minimal examp...

Xuhai Xu, et al. ∙

research

∙ 08/21/2019

PCRNet: Point Cloud Registration Network using PointNet Encoding

PointNet has recently emerged as a popular representation for unstructur...

Vinit Sarode, et al. ∙

research

∙ 02/03/2022

FORML: Learning to Reweight Data for Fairness

Deployed machine learning models are evaluated by multiple metrics beyon...

Bobby Yan, et al. ∙

research

∙ 11/17/2017

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

Accurate detection of objects in 3D point clouds is a central problem in...

Yin Zhou, et al. ∙

research

∙ 12/22/2016

Learning from Simulated and Unsupervised Images through Adversarial Training

With recent progress in graphics, it has become more tractable to train ...

Ashish Shrivastava, et al. ∙

research

∙ 06/12/2016

Neural Belief Tracker: Data-Driven Dialogue State Tracking

One of the core components of modern spoken dialogue systems is the beli...

Nikola Mrkšić, et al. ∙

research

∙ 12/26/2017

Actionable Email Intent Modeling with Reparametrized RNNs

Emails in the workplace are often intentional calls to action for its re...

Chu-Cheng Lin, et al. ∙

research

∙ 06/01/2017

Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules

Morphologically rich languages accentuate two properties of distribution...

Ivan Vulić, et al. ∙

research

∙ 03/02/2016

Counter-fitting Word Vectors to Linguistic Constraints

In this work, we present a novel counter-fitting method which injects an...

Nikola Mrkšić, et al. ∙

research

∙ 02/19/2018

Global Pose Estimation with an Attention-based Recurrent Network

The ability for an agent to localize itself within an environment is cru...

Emilio Parisotto, et al. ∙

research

∙ 02/19/2018

Divide, Denoise, and Defend against Adversarial Attacks

Deep neural networks, although shown to be a successful class of machine...

Seyed-Mohsen Moosavi-Dezfooli, et al. ∙

research

∙ 02/22/2018

Structured Control Nets for Deep Reinforcement Learning

In recent years, Deep Reinforcement Learning has made impressive advance...

Mario Srouji, et al. ∙

research

∙ 04/22/2018

Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching

Community-based question answering (CQA) websites represent an important...

Xiao Yang, et al. ∙

research

∙ 12/10/2018

Learning Sharing Behaviors with Arbitrary Numbers of Agents

We propose a method for modeling and learning turn-taking behaviors for ...

Katherine Metcalf, et al. ∙

research

∙ 04/02/2019

Mirroring to Build Trust in Digital Assistants

We describe experiments towards building a conversational digital assist...

Katherine Metcalf, et al. ∙

research

∙ 05/09/2019

Differentiable Approximation Bridges For Training Networks Containing Non-Differentiable Functions

Modern neural network training relies on piece-wise (sub-)differentiable...

Jason Ramapuram, et al. ∙

research

∙ 05/15/2019

Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models

Speech-driven visual speech synthesis involves mapping features extracte...

Ahmed Hussen Abdelaziz, et al. ∙

research

∙ 07/22/2019

On Modeling ASR Word Confidence

We present a new method for computing ASR word confidences that effectiv...

Woojay Jeon, et al. ∙

research

∙ 08/20/2019

Density estimation in representation space to predict model uncertainty

Deep learning models frequently make incorrect predictions with high con...

Tiago Ramalho, et al. ∙

research

∙ 08/26/2019

Connecting and Comparing Language Model Interpolation Techniques

In this work, we uncover a theoretical connection between two language m...

Ernest Pusateri, et al. ∙

research

∙ 08/30/2019

Single Training Dimension Selection for Word Embedding with PCA

In this paper, we present a fast and reliable method based on PCA to sel...

Yu Wang, et al. ∙

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